Abstract:

With the development of education technology, online learning has advanced into a new era of personalized and adaptive learning. Through applying emerging information and computing (IC) technologies to learning analytics and machine learning, we can now more precisely and accurately identify an individual learner’s style, behavior, strength and weakness, as well as more effectively and efficiently assess performance and progress. This is especially true in online education because big data about learners and their learning is readily available so that personalized and adaptive learning can be easily implemented to accommodate an individual learner’s style and behavior in order to largely remove learning barriers and reduce stress in the learning. It is aimed at enhancing learners’ performance and enabling learners to more effectively achieve course objectives and program learning outcomes prescribed by the curriculum. Therefore, students could complete their degrees in a learner-friendly and stress-free education.

However, when students come out of their learner-friendly education, they will have to face many real-life challenges. Their future occupations are unlikely to be personalized for them and the society will not necessarily adapt to their specific needs. Experiencing stress and difficulties during the training period acts as an important part of training to prepare for the real world. Although students may fail a course and experience stressful and difficulty, the consequences of this failure may be less detrimental than a similar failure in the workplace.

In this paper, we will present our introspection of personalized and adaptive learning and argue that it is the social and moral responsibility of educators and institutions to apply personalized and adaptive learning wisely in their educational practice. Educators and institutions should also recognize the realistic diversities of individual students’ learning styles and variable learning progress, contextually dependent learning accessibility, and their correspondent support needs for the fine-grained learning activities. We argue that the strategically balanced practices and innovated learning technology are crucial towards an optimized learning experience for the learners.

Keywords:

Personalized learning, Adaptive Learning, Learning Barriers, Social Responsibility.